- Hopefully at this point you have a very good ideaby now of how prescriptive analyticscan be one of the most important initiativesthat your organization can ever undertake,particularly if your organization is alreadyinvesting large amounts of money in big data,predictive analytics and other core technologies.Now though your job is to convince othersin your organization, executives, stakeholders,budget holders, of how importantprescriptive analytics actually are.Beware though, this will not be an easy sell for you.

In fact, here are some of the many objectionsthat you're likely to hear the first timeyou bring up the idea of prescriptive analyticsbut don't worry, we'll look at some powerfulcounter arguments for you in a moment.You may hear that prescriptive analyticsare just another trend, that it's way too earlyin the lifecycle for your organizationto spend any time or effort in this discipline.You may hear something along the lines of"We tried all this data-driven stuff in the past"and we've never really gotten any"business value out of it."Some people have a natural skepticism towardsnew concepts such as prescriptive analyticsand assume that they've only been inventedby consultants to sell customers expensivesystems that aren't really needed.

And especially if your company has alreadyinvested a large amount of money in big data,predictive analytics and other core technologies,the argument you might get on that point is,"What's so great about prescriptive analytics,"we're already doing a lot of this stuff anyway."Here's a list of counter arguments for you, point by point.If someone tells you that prescriptive analyticsare just another trend you can counter withthe argument that actually prescriptive analyticsare the convergence and culminationof a number of disciplines, many of whichhave been around for a while, all coming togetherwith incredible synergies with one another,and that's what we've put togetheras part of prescriptive analytics.

If someone tells you it's too earlyin the lifecyle to try prescriptive analyticsor to put any efforts into it, your naturalcounter argument would be that if you're makingany investments at all in analytics,this is where you need to be anyway,that if you aren't taking actions as a resultof those analytics, then why is the moneybeing spent in the first place?Over the years, as we've seen, many organizationshave had less than wonderful results with theirdata warehousing and their business intelligenceand there's a natural resistance to any effortsthat involve driving insight-sided data.

One of the points you should make thoughis that the past shortcomings have primarily beenbusiness-process-related and human-factors-related,far more so than technology and in factthat's one of the key advantagesof prescriptive analytics, and by followinga prescribed workflow you overcomea lot of those shortcomings and allowthe technology to do the job that it's able to do.A good counter argument to someone telling youthat prescriptive analytics are only inventedby consultants to sell expensive systemsis to try a small, high-value pilot projectfirst to prove out the concept.

Take one of your most critical business processesthat you're already doing analytical work inand then follow it all the way throughour prescriptive analytics workflow and seehow that works out over three months or six months,and then prove out the value that way.And finally, if you hear that all of theinvestments in big data and predictive analyticsare already there anyway, counter with the pointthat unless you get to the pointof prescriptive actions you're only producing insights,which may or may not have any business valueand may or may not ever lead to any action.

You can also sum up all of yourindividual counter arguments this way.If your organization is not confidentthat you can always take definitive actionbased on what's really happeningand what you're seeing in the data,you will be at a major competitive disadvantage.

Resume Transcript Auto-Scroll

Author

Released

5/13/2015

Everyone is talking about big data these days, but that's just the starting point for drawing high-value, actionable insights from your organization's data. This course takes viewers through the entire analytics lifecycle and workflow—beyond today's hype and buzzwords—and describes how any organization can turn their investments in big data into the actionable insights they really need. Author Alan Simon introduces today's relevant technologies and shows how best to apply them to specific business problems and opportunities within their organization. By the end of the course, viewers will understand how the different classes of analytics—descriptive, predictive, and discovery—can lead to prescriptive action.